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A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

:earth_americas: Extra Coordinate Systems, Geoms, Statistical Transformations & Scales for 'ggplot2'

Haplotype-aware CNV analysis from single-cell RNA-seq, ATAC-seq, and multiome

  • cancer-genomics
  • cnv-detection
  • single-cell
  • phylogeny